refactor(settings): update google api key environment variable name

Update environment variable name from GOOGLE_AI_API_KEY to GOOGLE_API_KEY for consistency
Remove redundant api_key parameter from Gemini model initialization
Comment out unused GRADIO_SHARE and GRADIO_DEBUG environment variables

Dockerfile

@@ -102,8 +102,8 @@ RUN chown -R app:app /app \
 ENV PYTHONPATH=/app
 ENV GRADIO_SERVER_NAME=0.0.0.0
 ENV GRADIO_SERVER_PORT=7860
-ENV GRADIO_SHARE=false
-ENV GRADIO_DEBUG=false
+# ENV GRADIO_SHARE=false
+# ENV GRADIO_DEBUG=false
 
 # Matplotlib configuration for headless operation
 ENV MPLBACKEND=Agg

config/settings.py

@@ -6,7 +6,7 @@ load_dotenv()
 
 
 class Settings:
-    GOOGLE_AI_API_KEY = os.getenv("GOOGLE_AI_API_KEY")
+    GOOGLE_AI_API_KEY = os.getenv("GOOGLE_API_KEY")
     MAX_FILE_SIZE_MB = 50
     SUPPORTED_FILE_TYPES = [
         "pdf",
@@ -46,8 +46,8 @@ class Settings:
 
     @classmethod
     def validate_config(cls):
-        if not cls.GOOGLE_AI_API_KEY:
-            raise ValueError("GOOGLE_AI_API_KEY required")
+        if not cls.GOOGLE_API_KEY:
+            raise ValueError("GOOGLE_API_KEY required")
         cls.TEMP_DIR.mkdir(exist_ok=True)
 
 

settings.py

@@ -6,7 +6,7 @@ load_dotenv()
 
 
 class Settings:
-    GOOGLE_AI_API_KEY = os.getenv("GOOGLE_AI_API_KEY")
+    GOOGLE_AI_API_KEY = os.getenv("GOOGLE_API_KEY")
     MAX_FILE_SIZE_MB = 50
     SUPPORTED_FILE_TYPES = [
         "pdf",
@@ -46,8 +46,8 @@ class Settings:
 
     @classmethod
     def validate_config(cls):
-        if not cls.GOOGLE_AI_API_KEY:
-            raise ValueError("GOOGLE_AI_API_KEY required")
+        if not cls.GOOGLE_API_KEY:
+            raise ValueError("GOOGLE_API_KEY required")
         cls.TEMP_DIR.mkdir(exist_ok=True)
 
 

workflow/financial_workflow.py

@@ -71,7 +71,7 @@ class FinancialDocumentWorkflow(Workflow):
     
     # Data Extractor Agent - Structured output eliminates JSON parsing issues
     data_extractor: Agent = Agent(
-        model=Gemini(id=settings.DATA_EXTRACTOR_MODEL,thinking_budget=settings.DATA_EXTRACTOR_MODEL_THINKING_BUDGET,api_key=settings.GOOGLE_AI_API_KEY),
+        model=Gemini(id=settings.DATA_EXTRACTOR_MODEL,thinking_budget=settings.DATA_EXTRACTOR_MODEL_THINKING_BUDGET),
         description="Expert financial data extraction specialist",
         instructions=[
                 "Extract comprehensive financial data from documents with these priorities:",
@@ -141,7 +141,7 @@ class FinancialDocumentWorkflow(Workflow):
     
     # Data Arranger Agent - Organizes data into categories for Excel
     data_arranger: Agent = Agent(
-        model=Gemini(id=settings.DATA_ARRANGER_MODEL,thinking_budget=settings.DATA_ARRANGER_MODEL_THINKING_BUDGET,api_key=settings.GOOGLE_AI_API_KEY),
+        model=Gemini(id=settings.DATA_ARRANGER_MODEL,thinking_budget=settings.DATA_ARRANGER_MODEL_THINKING_BUDGET),
         description="Financial data organization and analysis expert", 
         instructions=[
             'Organize the extracted financial data into logical categories based on financial statement types (Income Statement, Balance Sheet, Cash Flow Statement, etc.).',
@@ -181,8 +181,7 @@ class FinancialDocumentWorkflow(Workflow):
     code_generator = Agent(
         model=Gemini(
             id=settings.CODE_GENERATOR_MODEL,
-            thinking_budget=settings.CODE_GENERATOR_MODEL_THINKING_BUDGET,
-            api_key=settings.GOOGLE_AI_API_KEY
+            thinking_budget=settings.CODE_GENERATOR_MODEL_THINKING_BUDGET
         ),
         description="Excel report generator that analyzes JSON data and creates formatted workbooks using shell execution on any OS",
         goal="Generate a professional Excel report from arranged_financial_data.json with multiple worksheets, formatting, and charts",